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Design Process of Agriculture Ontologies

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Talk at International Symposium on Designing Semantics
15March, 2017, Kyoto, Japan.

Published in: Technology
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Design Process of Agriculture Ontologies

  1. 1. Hideaki Takeda National Institute of Informatics (NII) International Symposium on Designing Semantics 15March, 2017, Kyoto, Japan Design Process of Agriculture Ontologies
  2. 2. Standardization of Agricultural Activities  Background  Issues  Purpose Agricultural IT systems are widely adopted to manage and record activities in the fields efficiently. Interoperability among these systems is needed to integrate and analyze such records to improve productivity of agriculture. To provide the standard vocabulary by defining the ontology for agricultural activity Data in agricultural IT systems is not easy to federate and integrate due to the variety of the languages It prevents federation and integration of these systems and their data. http://www.toukei.maff.go.jp/dijest/kome/kome05/kome05.html しろかき “Puddling” 砕土 “Pulverization” 代かき “Puddling” 代掻き “Puddling” 代掻き作業 “Puddling Activity” 荒代(かじり) “Coarse pudding” 荒代かき “Coarse pudding” 整地 “Land grading” 均平化 “land leveling”
  3. 3.  Define activity concepts  Define hierarchy Seeding: activity to sow seeds on fields for seed propagation. Purpose: seed propagation Place : field Target : seed Act : sow “Seeding” Define activities with properties and their values The hierarchy of activities is organized by property - New properties and their values are added - “purpose”, “act”, “target”, “place”, “means” , “equipment”, “season”, and “crop” in order. - Property values are specialized Seeding property value Agricultural Activity Ontology(AAO)
  4. 4.  Formalization by Description Logics Crop production activity Crop growth activity purpose:crop production purpose:crop growth Agricultural activity Activity for control of propagation Activity for seed propagation purpose:control of propagation purpose:seed propagation Seeding act : sow target:seed place:field Activity for seed propagation Seeding Designing of Agricultural Activity Ontology(AAO)
  5. 5.  Differentiate concepts by property purpose : seed propagation place : paddy field target : seed act : sow crop:rice purpose : seed propagation purpose : seed propagation place : field target : seed act : sow Agricultural activity >…> Activity for seed propagation > Seeding purpose : seed propagation place : well-drained paddy field target : seed act : sow crop:rice Direct sowing of rice on well-drained paddy field Direct seeding in flooded paddy field Well-drained paddy field < field paddy field < field Designing of Agricultural Activity Ontology(AAO)
  6. 6. Activity for seeding Direct seeding in flooded paddy field Direct sowing of rice on well-drained paddy field Seeding on nursery box  The Structuralizaion of the Agricultural Activities (Protégé) Designing of Agricultural Activity Ontology(AAO)
  7. 7.  Polysemic concepts [disjunction form] [conjunction form] Pudlling Subsoil breaking PulverizationLand preparation Water retention Activity for water management Land leveling Polysemic relationship Pulverization by harrow purpose : pulverization purpose : water retention purpose : land leveling Definition of agriculture activities with multiple purposes or other properties. Puddling Designing of Agricultural Activity Ontology(AAO)
  8. 8. Water retention Land leveling Pulverization Puddling  Polysemic concepts (Protégé) Designing of Agricultural Activity Ontology(AAO)
  9. 9.  Synonym Designing of Agricultural Activity Ontology(AAO) Expressions in multiple languages are also represented as synonyms. (It is important especially for non-English speaking countries)
  10. 10.  Reasoning by Ontology Reasoning by Agriculture Activity Ontology Activity for biotic control Activity for suppression of pest animals Activity for suppression of pest animals by physical means control of pest animals Physical means means (0,1) purpose (0,1) Biotic control purpose(0,1) Activity for suppression of pest animals by chemical means Chemical means purpose (0,1) means (0,1) Making scarecrow‘ suppression of pest animals Purpose (0,1) build act (0,1) scarecrow target (0,1) Physical means Means (0,1) ? Example of「Making scarecrow」 ? suppression of pest animals Infer the most feasible upper concept for the given constraints for a new words
  11. 11.  Reasoning by Ontology かかし作り 物理的手段 means (0,1) means (0,1) Inference with SWCLOS [1] Seiji Koide, Theory and Implementation of Object Oriented Semantic Web Language, PhD Thesis, Graduate University for Advance Studies, 2011 [1] [1] Activity for biotic control Activity for suppression of pest animals Activity for suppression of pest animals by physical means control of pest animals Physical means means (0,1) purpose (0,1) Biotic control purpose(0,1) suppression of pest animals Activity for suppression of pest animals by chemical means Chemical means purpose (0,1) means (0,1) Making scarecrow make act (0,1) scarecrow target (0,1) Infer the most feasible upper concept for the given constraints for a new words Reasoning by Agriculture Activity Ontology Making scarecrow is a subclass of Activity for suppression of pest animals by physical means
  12. 12. Applying Agricultural Activity Ontology  URI Give a unique URI for each concept http://cavoc.org/aao/ns/1/は種
  13. 13. http://www.cavoc.org/ http://www.cavoc.org/aao Web Services based on Agriculture Activity Ontology • Version History ver. 141: published on January 5, 2017. 410 words and concepts. ver 1.33: published on September 23, 2016. 374 words and concepts, ver 1.31 : published on April 22, 2016. 355 words collected, the concepts were classified with 8 attributes. ver 1.10 : published on February 12, 2016. 330 words collected, new words are collected. ver 1.00 : published on November 2, 2015. 301 words collected, defined with Description Logics, introduction of property. ver 0.94 : published on May 12, 2015. 185 words collected.
  14. 14. Web Services based on Agriculture Activity Ontology  Data Sharing The data of AAO can be downloaded in the RDF/Turtle formats from cavoc.org/aao/. we provide a SPARQL endpoint for users to explore AAO data using SPARQL queries. [the SPARQL Endpoint of AAO][Download]
  15. 15. Web Services based on Agriculture Activity Ontology  Converting synonyms to core vocabulary http://www.tanbo-kubota.co.jp/foods/watching/14_2.html “Puddling Activity” “sowing” … AAO Puddling Seeding … Converting [system] API Puddling Activity and sowing… [system’] Puddling and seeding…
  16. 16. How did we build Agriculture Activity Ontology? • Share the experience of building ontologies • Design Process – 0th Step: Project Formation – 1st Step: Survey – 2nd Step: Analysis of Data – 3rd Step: Proposed Structure (1st) – 4th Step: Introduction of Descriptions Logics – 5th Step: Evaluation and Enrichment by domain experts
  17. 17. Design Process - 0th Step: Project Formation - • Cross-ministerial Strategic Innovation Promotion Program (SIP), “Technologies for creating next-generation agriculture, forestry and fisheries” (funding agency: Bio-oriented Technology Research Advancement Institution, NARO). • Project aim: define common vocabulary on agriculture activity – To share knowledge among farmers of different crops and different regions and different systems – Human understandable and machine readable • Four members from two organizations – Ontology Expert Researchers from National Institute of Informatics (NII) – Information Expert Researchers from National Agriculture and Food Organization (NARO)
  18. 18. Design Process - 1st Step: Survey - • Survey of existing vocabularies – Agrovoc: defined by FAO. Most popular and famous vocabulary in the domain • International • Maintenance • Machine readable (LOD) – Agropedia • In Japanese • With explanations – MAFF Guideline (prototype version) • Official • Related to Elements in Official Statistics
  19. 19. AGROVOC  Thesaurus AGROVOC organizes words by synonym, narrower/broader, and related relationship. harvesting topping(beets) baling gleaning mechanical harvesting mowing AGROVOC . . . Narrower/broader relationship is not clearly defined. So relationship among bother words are often mixed and misunderstood. relationship between siblings AGROVOC is the most well-known vocabulary in agriculture supervised by Food and Agriculture Organization(FAO) and the thesaurus containing more than 32,000 terms of agriculture, fisheries, food, environment and other related fields. The number of activity names about rice farming, which is important in Asia including Japan, are insufficient.
  20. 20. 農業ITシステムで用いる農作 業の名称に関する個別ガイ ドライン(試行版)
  21. 21. Design Process - 2nd Step: Analysis of data
  22. 22. Design Process - 3rd Step: Proposed Structure (1st) -  Define hierarchy clearly  Accept various synonymous words Hierarchy is convenient for human to understand and for computers to process. But it often be confused by mixing different criteria on relationship among concepts/words. It causes difficulty when adding new concepts/words and when integrating different hierarchies. Names for a single concept may be multiple by region and by crop Define relationship clearly between upper and lower concepts as basis of classification Clarify an entry word and their synonyms for each concept harvesting topping(beets) baling gleaning mechanical harvesting mowing Thesaurus (AGROVOC) . . . harvesting mechanical harvesting manual harvesting . . . Inheritrelationship between siblings Representation: ”Harvesting”
  23. 23. Design Process - 4th Step: Introduction of Description Logics - • Consideration of the structure – Discovery of logical structure – Reformation of the structure by Description Logics • Use of a property for each is-a relation – Introduction of a new property – Is-a hierarchy of a property value • Re-arrangement of classes harvesting mechanical harvesting manual harvesting . . . Harvest Harvest Harvest Inherit byMachine manually + + Representation: ”Harvesting” [Act] Ontology harvesting mechanical harvesting manual harvesting . . . Representation: ”Harvesting” [Means] [Means]
  24. 24. Design Process - 5th Step: Evaluation and Enrichment by domain experts - • Ask evaluations to experts – individual crops experts – Farmer management system developer • Feedback – Some alternation of class structure – Many new words • Crop-specific words • Area-specific words (dialect)
  25. 25. What we’ve learnt • Survey and critics of existing vocabularies – Understanding of pros and cons – Fix the target • Data-driven approach – Avoid too abstract discussion • Small group of knowledgeable persons of two sides (domain and informatics) – Constructive discussion • Make the core then extend it – Introduction of AI experts – Introduction of more domain experts • Communication is important
  26. 26. Crop Vocabulary (CVO) • Next target: Standardize crop names – ジャガイモ(jagaimo), 馬鈴薯(bareisho) poteto@en – 大豆(daizu), 枝豆(edamame), soy@en – … • Crop Concept – Crop name • Synonym – Japanese common name • Scientific name – Edible part – Mature/Immature – Other properties • Planting method …
  27. 27. Data-driven Crop names for agricultural chemicals Guideline name (2017) CVO Guideline name (2016) Crop statistics Household budget survey Vegetable Code MAFF Encourage varieties Food classifi -cation
  28. 28. http://cavoc.org/ Common Agricultural VOCabulary Agriculture Activity Ontology (AAO) ver 1.31 http://cavoc.org/aao/ Conclusion There are no gold way to build ontologies. We adopt the bottom-up and minimum commitment approach. It requires time and effort. We believe that it is successful at least to build AAO.

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